Long-range prediction and the stratosphere

Détails

Ressource 1Télécharger: acp-22-2601-2022.pdf (1790.68 [Ko])
Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_1B7B5AE26D02
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Long-range prediction and the stratosphere
Périodique
Atmospheric Chemistry and Physics
Auteur⸱e⸱s
Scaife Adam A., Baldwin Mark P., Butler Amy H., Charlton-Perez Andrew J., Domeisen Daniela I. V., Garfinkel Chaim I., Hardiman Steven C., Haynes Peter, Karpechko Alexey Yu, Lim Eun-Pa, Noguchi Shunsuke, Perlwitz Judith, Polvani Lorenzo, Richter Jadwiga H., Scinocca John, Sigmond Michael, Shepherd Theodore G., Son Seok-Woo, Thompson David W. J.
ISSN
1680-7324
Statut éditorial
Publié
Date de publication
25/02/2022
Peer-reviewed
Oui
Volume
22
Numéro
4
Pages
2601-2623
Langue
anglais
Résumé
Over recent years there have been concomitant advances in the development of stratosphere-resolving numerical models, our understanding of stratosphere–troposphere interaction, and the extension of long-range forecasts to explicitly include the stratosphere. These advances are now allowing for new and improved capability in long-range prediction. We present an overview of this development and show how the inclusion of the stratosphere in forecast systems aids monthly, seasonal, and annual-to-decadal climate predictions and multidecadal projections. We end with an outlook towards the future and identify areas of improvement that could further benefit these rapidly evolving predictions.
Mots-clé
Atmospheric Science
Web of science
Open Access
Oui
Financement(s)
Fonds national suisse / PP00P2_170523
Fonds national suisse / PP00P2_198896
Création de la notice
08/03/2022 15:12
Dernière modification de la notice
10/07/2024 7:05
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